NVIDIA makes the microchips the world needs to power Artificial Intelligence, and the surge in demand as the technology has spread has made it the world’s most valued company. Its rise to a market value of over $3.333tn has been fast. It came just two months after it reached the $2tn milestone and was driven by its dominance over the advanced graphics processing unit chips, or GPUs, on which AI depends.
The company’s name is blended from the Latin word for envy – invidia – and the acronym NV, which stands for Next Vision. It has been living up to the ambition this sets out.
Strategic financial manoeuvres and continuous product innovation have solidified its leading position in the AI chip market and sent it to the peak of the stock market. It has surpassed the market capitalisation of Microsoft, which is at $3.303tn and in second place. Apple is in third, with $3.222tn. The Middle East’s biggest company, Saudi Aramco, has a market capitalisation of $1.788tn.
Microsoft remains within touching distance of the top spot, and market fluctuations mean it can change hands. While analysts expect NVIDIA to hold on to the top spot, on Monday, 24 June, NVIDIA shares fell by 6.7% due to profit-taking, contributing to a three-day decline of 16% and impacting the broader semiconductor and tech sectors. For example, Taiwan's benchmark index dropped nearly 2% on Monday, marking its largest fall in two months, while blue-chip company TSMC saw a loss of over 3%.
However, share prices could bounce back, especially since NVIDIA announced a stock split to make shares more accessible to individual investors. Historically, such tactics have helped achieve a positive stock performance, boosting investor confidence and growth potential.
Advantages and challenges
Since its inception in 1993, NVIDIA has been highly innovative, and its GPUs have capabilities that mean the company has significantly expanded its market share to become a major force in the global tech industry and a stock market powerhouse. NVIDIA's Compute Unified Device Architecture software system—CUDA—gives it an advantage that its competitors have struggled to match. It has become an industry standard system.
NVIDIA’s GPUs are renowned for their superior performance. It has brand loyalty in gaming and professional markets, and there is demand for its products from companies of all sizes, from start-ups to multinationals. It is known for its substantial investment in research and development, which has helped it build a reputation for cutting-edge innovation— further boosting its credentials in the fast-moving AI world.
Fierce competition
Nonetheless, NVIDIA is in a fiercely competitive sector. The semiconductor industry contains established rivals such as Advanced Micro Devices (AMD) and Intel. Some of the biggest names in the wider world tech industry have become new entrants in the chip-making sector, including Google, which is developing its own AI semiconductors.
This means that NVIDIA faces constant challenges in its market share. Meanwhile, competition over supply chains, disrupted by geopolitical tension, creates worries over potential product delays and increased costs. NVIDIA’s main AI and gaming markets are volatile, with risks of shifts in consumer demand and vulnerability to technological advancements from competitors.
The company’s growth has also been driven by acquisitions, although it failed in its attempt to buy the major chip designer Arm Holdings, thwarted by regulatory concerns. Such setbacks can impact strategic planning and market confidence.
Blackwell to the future
At a recent major industry event—the GPU Technology Conference (GTC) 2024—NVIDIA CEO Jensen Huang highlighted the transformative impact of AI on systems across industries. NVIDIA introduced its latest GPU architecture, Blackwell, which represents a significant leap in computational power and data management for enterprises.
With 208 billion transistors, Blackwell is designed to handle the vast datasets required for large language models (LLMs). However, transitioning to AI-centric systems involves considerable challenges, particularly the costs associated with establishing the necessary infrastructure. Companies must strategically plan their AI investments to maximise returns.
